Reactive programming is used for constructing case-oriented systems that are scalable, tolerant of failure and high responsive despite the loading and failure (The Reactive Manifesto).
Examples of data streams:
- System operation protocols;
- Hardware operation data, including the Internet of Things;
- Service calls;
- Clicks of users;
- Tweets in Social Networks.
Possibilities of data streams processing:
- Extracting of interesting cases from the total stream;
- Cases correlation
- Calculations including the estimation of system status (for example, the number of hardware failures within given time period);
- Following/ not following the pattern of cases appearance (for example, closing of the session without its opening), which can mean an attempt of hacker attack.
Reactive programming areas of application:
- Finance – for algorihtmization of trade and searching of fraud;
- Telecommunication – for monitoring of network and service quality;
- Production – for data monitoring (RFID), data aggregating from sensors and alarm raising in case of failures;
- Web applications — for website traffic analysis and identification of improper behavior;
- Healthcare – for patient’s health condition analysis;
- Logistics – for forecasting and controlling of supply chain and GPS-tracking;
- Security systems/ Smart home/ Automobile telemetrics.
Lightbend Fast Data Platform
is a full function application platform for transferring from traditional Big Data architecture to new Fast Data architecture, where the data streaming is the main abstraction.
Lightbend Fast Data Platform includes the solutions from leading suppliers for data streaming systems and reactive systems:
- Apache Kafka;
- Apache Spark;
- Mesosphere DC/OS;
- Apache Flink;
- Lightbend Reactive Platform (Akka, Akka Streams, Play, Lagom Frameworks).
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